Lifestyle Diseases

Semester II CVAC Lifestyle Diseases and their Prevention Syllabus Introduction to Lifestyle Diseases: Definitions and classifications Causes and consequences of obesity...

Semester II CVAC Lifestyle Diseases and their Prevention Syllabus Introduction to Lifestyle Diseases: Definitions and classifications Causes and consequences of obesity Diabetes mellitus: types, risk factors, and management. Cardiovascular Diseases: Heart disease and hypertension Role of diet and exercise in heart Health Introduction to Lifestyle Diseases: Definitions and classifications Definitions Lifestyle diseases are defined as diseases linked with the way people live their life. These are non-communicable diseases. This is commonly caused by lack of physical activity, unhealthy eating, alcohol, drugs and smoking. Lifestyle disorders are the major health issues observed all over the world. They can be defined as Lifestyle disorders are the major health issues found all over the world. The world is shifting from infectious diseases to non-communicable diseases (NCDs) (Mathur & Mascarenhas, 2019). Increased modernization and industrialization has impacted the lifestyle. According to World Health Organization (WHO) report, the mortality rate has increased in the countries with low economic status and poverty due to NCDs (Tabish, 2017). Prevalence of communicable and non- communicable diseases has increased in India. With the increased industrialization, jobs and professions have changed the lifestyle of an individual and adults are more susceptible to the risk of chronic diseases. Also the quality of food has been decreased due to poor soil mineralization and increased processing techniques. A recent study from various locations in India shows that people with lower socioeconomic status are more likely to develop coronary heart disease and have a higher death rate (Singh, Fernandes, Sarkar & Sridevi, 2019). Diseases that are associated with the lifestyle of an individual or the way of living are known as lifestyle disorders. Also termed as non-communicable diseases (NCDs) as they do not transmit from one person to another when diagnosed. These are chronic in nature and are often caused due to unhealthy lifestyle, undesirable behaviour, chronic stress, poor dietary habits, physical inactivity and addiction to alcohol, smoking and social media. Most of them are not curable but can be controlled and prevented if proper nutrition and necessary changes were made into the lifestyle. They are the most leading cause of death all around the world. NCDs require a prolonged course of treatment and have multiple risk factors and complex etiology (Balwan & Kour, 2021). NCDs like diabetes, cancer, CVDs and respiratory diseases are closely linked with the choices in lifestyle and hence they are termed as lifestyle disorders. NCDs like diabetes, cancer, CVDs and respiratory diseases are closely linked with the choices in lifestyle and hence they are termed as lifestyle disorders. Characteristics of non-communicable diseases (NCD’S): Lifestyle diseases are characterised by the following – 1  i. Complex etiology: Non-communicable diseases have multiple risk factors. It is impossible to determine the exact cause of lifestyle diseases. The etiology of NCDs can be divided into two subcategories: uncontrollable causes (rapid unplanned modernization, globalisation of unhealthy ifestyles and population aging) and controllable causes (raised blood pressure, increased blood sugar levels, elevation of blood lipid levels and central obesity). ii. Non-contagious (non-communicable): Lifestyle disorders are non- infectious diseases that are related to one’s lifestyle. iii. Prolonged course of illness: NCDs require long-term course of medical treatment as they are chronic in nature. iv. Functional impairment or disability: NCDs cause functional impairment or disability and makes it difficult for the patient to live a normal life. Patients with chronic disorders are unable to participate in regular physical activities and eat normally (Tabish, 2017). Causes of NCDs Factors that contribute to the development of NCDs are classified into the following categories – i. Modifiable risk factors: Factors that are related to one’s behaviour are known as modifiable behavioural risk factors. It includes excessive consumption of alcohol, addiction to smoking and tobacco, physical inactivity, wrong body posture and disturbed biological clock. Sedentary lifestyle as table work and stress related work also increases the occurrence of NCDs. ii. Non- Modifiable risk factors: Factors that cannot be controlled or modified with the application of intervention are known as non- modifiable risk factors. These include age, race, gender and genetics. iii. Metabolic risk factors: Factors that increase the possibility of NCDs by causing certain changes in the metabolism are known as metabolic risk factors. These include increased blood pressure, obesity, hyperglycaemia, and hyperlipidemia (Balwan & Kour, 2021). Classifications of Lifestyle Diseases OBESITY (Causes and consequences of obesity) Over the past four decades, the prevalence of overweight and obesity in the United States has increased dramatically (Flegal, Carroll, Kuczmarski, & Johnson, 1998). More than half of all Americans are now overweight or obese (Mokdad et al., 1999), and the trend toward increasing prevalence has not abated (Mokdad et al., 2000). Concern about this epidemic-like trend stems from an overwhelming body of evidence demonstrating the negative health consequences associated with increased body weight. Being overweight or obese substantially raises the risk for a variety of illnesses, and excess weight is associated with increased all-cause mortality (Pi-Sunyer, 1999). Consequently, millions of Americans stand poised to develop weight-related illnesses such as cardiovascular disease, hypertension, diabetes mellitus, and osteoarthritis. As the second leading contributor to preventable death in the United States (McGinnis & Foege, 1993), obesity constitutes a major threat to public health and a significant challenge to health care professionals. 2 CLASSIFICATION OF OBESITY Obesity is defined as an excessive accumulation of body fat, excessive to the extent that it is associated with negative health consequences. An individual is considered obese when body fat content equals or exceeds 30% to 35% in women or 20% to 25% in men (Lohman, 2002). Body Mass Index Body Mass Index (BMI), also known as Quetelet’s Index, is an alternative weight-to-height ratio that has gained general acceptance as the preferred method for gauging overweight. BMI is calculated by dividing weight in kilograms by the square of height in meters (kg/m2). The WHO Classification System The WHO (1998) has developed a graded classification system for categorizing overweight and obesity in adults according to BMI. In the WHO system, overweight is defined as a BMI >25, and obesity is defined as a BMI > 30. The WHO system, which has also been accepted by NIH (NHLBI, 1998), employs six categories based on the known risk of comorbid conditions associated with different BMI levels. For example, the risk of comorbid conditions is considered average in the normal weight category and very severe in the obese class III category. Thus, the WHO classification system facilitates the identification of individuals and groups at increased risk of morbidity and mortality, and it allows for meaningful comparisons of weight status within and between populations. World Health Organization Classification of Overweight, according to BMI and Risk of Comorbidities Category BMI (kg/m2) Disease Risk Underweight < 18.5 Low* Normal weight 18.5…24.9 Average Overweight = /> 25.0 Pre-obese 25.0…29.9 Increased Obese Class I 30.0…34.9 Moderate Obese Class II 35.0…39.9 Severe Obesity Class III = /> 40.0 Very severe Prevalence Obesity affects some groups more than others – The obesity prevalence was 39.8% among adults aged 20 to 39 years, 44.3% among adults aged 40 to 59 years, and 41.5% among adults aged 60 and older. Statistics show over 1.25 crore children aged 5 to 19 are overweight, up from 40 lakh in 1990. Obesity among children in India has rapidly increased. Statistics from 2022 indicate that around 1.25 crore children aged 5 to 19 years are overweight compared to normal. CONSEQUENCES OF OBESITY Impact on Morbidity Obesity has a substantial adverse impact on health via its association with a number of serious illnesses and risk factors for disease. Obesity-related conditions include hypertension, dyslipidemia, type 2 diabetes mellitus, coronary heart disease (CHD), stroke, gallbladder disease, osteoarthritis, sleep apnea, respiratory problems, and cancers of the endometrium, breast, 3 prostate and colon. Some of the more prominent comorbidities of obesity are described hereunder. Hypertension. The prevalence of high blood pressure in adults is twice as high for individuals with BMI 30 than for those with normal weight (Dyer & Elliott, 1989; Pi-Sunyer, 1999). Mechanisms for increased blood pressure appear to be related to increases in blood volume, vascular resistance, and cardiac output. Hypertension is a risk factor for both CHD and stroke (Havlik, Hubert, Fabsitz, & Feinleib, 1983). Dyslipidemia. Obesity is associated with lipid profiles that increase risk for CHD, including elevated levels of total cholesterol, triglycerides, and low-density lipoprotein (bad) cholesterol, as well as low levels of high density lipoprotein (good) cholesterol (Allison & Saunders, 2000). Type 2 Diabetes Mellitus. Data from international studies consistently show that obesity is a robust predictor of the development of diabetes (Folsom et al., 2000; Hodge, Dowse, Zimmet, & Collins, 1995; NHLBI, 1998). A 14-year prospective study concluded that obese women were at 40 times greater risk for developing diabetes than normal weight, age-matched counterparts (Colditz et al., 1990). Current estimates suggest that 27% of new cases of type 2 diabetes are attributable to weight gain of 5 kg or more in adulthood (Ford,Williamson, & Liu, 1997). Moreover, abdominal obesity is a specific major risk factor for type 2 diabetes (Chan, Rimm, Colditz, Stampfer, & Willett, 1994). Coronary Heart Disease. Overweight, obesity, and abdominal adiposity are associated with increased morbidity and mortality due to CHD. These conditions are directly related to elevated levels of cholesterol, blood pressure, and insulin, all of which are specific risk factors for cardiovascular disease. Recent studies suggest that, compared to a BMI in the normal range, the relative risk for CHD is twice as high at a BMI of 25 to 29, and three times as high for BMI 29 (Willett et al., 1995). Moreover, a weight gain of 5 to 8 kg increases CHD risk by 25% (NHLBI, 1998; Willett et al., 1995). Stroke. The Framingham Heart Study (Hubert, Feinleib, McNamara, & Castelli, 1983) suggested that overweight may contribute to stroke risk, independent of hypertension and diabetes. Later research established that the relationship between obesity and stroke is clearer for ischemic stroke versus hemorrhagic stroke (Rexrode et al., 1997). Recent prospective studies show a graduated increase in risk for ischemic stroke with increasing BMI (i.e., risk is 75% higher with BMIs 27; 137% higher with BMIs 32) (Rexrode et al., 1997). Gallstones. Obesity is a risk factor across both age and ethnicity for gallbladder disease. The risk of gallstones is 4 to 6 times higher for women with BMIs 40 compared to women with BMIs 24 (Stampfer, Maclure, Colditz, Manson, & Willett, 1992). 4 Sleep Apnea. Sleep apnea is a serious and potentially life-threatening breathing disorder, characterized by repeated arousal from sleep due to temporary cessation of breathing. Both the presence and severity of sleep apnea is associated with obesity, and sleep apnea occurs disproportionately in people with BMIs >30 (Loube, Loube, & Miller, 1994). Large neck circumference (>/= 17 inches in men and >/=16 inches in women) is highly predictive of sleep apnea (Davies & Stradling, 1990). Women’s Reproductive Health. Menstrual irregularity and amenorrhea are observed with greater frequency in overweight and obese women (Hartz, Barboriak, Wong, Katayama, & Rimm, 1979). Polycystic ovary syndrome, which often includes infertility, menstrual disturbances, hirsutism (growth of excessive male-pattern hair in women after puberty), and anovulation (not ovulating or releasing an egg), is associated with abdominal obesity, hyperinsulinemia (the amount of insulin in the blood is higher than what's considered healthy), and insulin resistance (the body's cells don't respond normally to insulin. Glucose can't enter the cells as easily, so it builds up in the blood. This can eventually lead to type 2 diabetes) (Dunaif, 1992; Goudas & Dumesic, 1997). Impact on Mortality Not only does obesity aggravate the onset and progression of some illnesses, it also shortens life (Allison, Fontaine, Manson, Stevens, & Van Itallie, 1999). Studies show that all-cause mortality rates increase by 50% to 100% when BMI is equal to or greater than 30 as compared with BMIs in the normal range (Troiano, Frongillo, Sobal, & Levitsky, 1996). Indeed, more than 300,000 deaths per year in the United States are attributable to obesity-related causes (Allison et al., 1999). Psychosocial Consequences Many obese people experience social discrimination and psychological distress as a consequence of their weight. The social consequences associated with obesity include bias, stigmatization, and discrimination consequences that can be highly detrimental to psychological well-being (Stunkard & Sobal, 1995). Social bias results from the widespread, but mistaken, belief that overweight people lack self-control. Negative attitudes toward obese people, which are pervasive in our society, have been reported in children as well as adults, in health care professionals as well as the general public, and in overweight individuals themselves (Crandall & Biernat, 1990; Rand & Macgregor, 1990). An obese person is less likely to get into a prestigious college, to get a job, to marry, and to be treated respectfully by a physician than is his or her non-obese counterpart (Gortmaker, Must, Perrin, Sobol, & Dietz, 1993; Pingitore, Dugoni, Tindale, & Spring, 1994). Indeed, obesity may well be the last socially acceptable object of prejudice and discrimination in our country. Despite the negative social consequences of being overweight, most early studies have reported similar rates of psychopathology in obese and non-obese individuals. However, these studies suffered from a number of limitations, for example, failing to account for gender effects (Wadden, Womble, Stunkard, & Anderson, 2002). More recent studies have attempted to rectify this. Alarge-scale, general population study (Carpenter, Hasin, Allison, & Faith, 2000) recently showed that obesity was associated with a 37% greater risk of major depressive 5 disorder, as well as increased suicidal ideation and suicide attempts among women but interestingly, not among men, for whom obesity was associated with a reduced risk of major depression. A consistent finding is the higher levels of body image dissatisfaction that are widely reported by obese individuals. Body image dissatisfaction is particularly elevated in women with higher socioeconomic status, those who were overweight as children, and binge eaters (French, Jeffery, Sherwood, & Neumark-Sztainer, 1999; Grilo, Wilfiey, Brownell & Rodin, 1994). In contrast, members of certain minority groups, particularly, Hispanic and African Americans, are less likely to display disparaging attitudes toward obesity in either themselves or others (Crandall & Martinez, 1996; Kumanyika, 1987; Rucker & Cash, 1992). In fact, Black women often ascribe positive attributes such as stamina and authority to being large (Rosen & Gross, 1987). In contrast to studies of obese persons in the general population, research on psychological disturbance in people presenting for treatment at obesity clinics shows a clear pattern of results. Obese help-seekers display higher rates of psychological distress and binge eating when compared to normal weight individuals and to obese persons who are not seeking help (Fitzgibbon, Stolley, & Kirschenbaum, 1993; Spitzer et al., 1993). Economic Costs of Obesity The economic impact of obesity is enormous. In 1995, the total costs attributable to obesity amounted to $99.2 billion (Wolf & Colditz, 1998). This total can be further viewed in terms of direct and indirect costs. Direct costs (i.e., dollars expended in medical care due to obesity) amount to approximately $51.6 billion and represent 5.7% of national health expenditures in the United States. The indirect costs (i.e., lost productivity due to morbidity and mortality from diseases associated with obesity) amount to an additional $47.6 billion. In addition, consumers spend in excess of $33 billion annually for weight-loss interventions, exercise programs, weight control books, and diet foods and beverages (Thomas, 1995). Researchers estimate that the overall economic impact of obesity is similar to that of cigarette smoking (NHLBI, 1998; Wolf & Colditz, 1998). CONTRIBUTORS TO OBESITY Given the prevalence and seriousness of obesity, it is essential that we understand its etiology. Understanding the factors that contribute to the development of obesity may lead to effective interventions for its control and prevention. Here, we address genetic and environmental contributors to overweight and obesity. Genetic Contributors In the past decade, there has been great enthusiasm about the prospects of identifying the biological causes of obesity. A body of research showing that obesity tends to run in families spurred the search for the genetic basis of obesity. For example, familial studies consistently have shown that BMI is highly correlated among first-degree relatives (Bouchard, Perusse, Leblanc, Tremblay, & Theriault, 1988), and investigations of identical twins reared apart have suggested that the genetic contribution to BMI may be as high as 70% (Stunkard, Harris, Pedersen, & McClearn, 1990). Such findings have led researchers to suspect that a single major, but as yet unidentified, recessive gene accounts for a significant proportion of the variance in body mass (Bouchard, Perusse, Rice, & Rao, 1998). In addition, researchers also believe that body-fat distribution, resting metabolic rate, and weight gain in response to overconsumption are 6 each controlled by genetic factors that may interact to predispose certain individuals to obesity (Chagnon et al., 2000; Feitosa et al., 2000; Levin, 2000). Among the first genetic defects linked to obesity was the discovery of the ob gene and its protein product leptin (Zhang et al., 1994). Leptin, a hormone produced by fat cells, influences hypothalamic regulation of energy intake and expenditure. Laboratory mice that fail to produce leptin due to a genetic defect become obese as the result of excess energy intake and physical inactivity (Zhang et al., 1994). Moreover, the administration of recombinant leptin in such animals decreases food intake, increases physical activity, and reduces body weight (Campfield, Smith, Guisez, Devos, & Burn, 1995). In humans, however, only a very small percentage of obese individuals have leptin deficiencies (Montague et al., 1997). Most obese individuals actually have higher rather than lower levels of leptin due to their higher levels of adipose tissue (Considine et al., 1996). Thus, some researchers (Ahima & Flier, 2000) have suggested that obese persons may become leptin resistant similar to the way obese persons with type 2 diabetes become insulin resistant. Trials of recombinant leptin as treatment for obesity have yielded modest results. High doses of leptin (administered via daily subcutaneous injections) have produced reductions in body weight of about 8%, a decrease equivalent to what is typically accomplished in lifestyle interventions (Heymsfield et al., 1999). Several other single-gene defects have been discovered that contribute to obesity in animals (Collier et al., 2000; Levin, 2000). However, only one of these mutations appears to be a frequent contributor to human obesity. Investigators (Farooqi et al., 2000; Vaisse et al., 2000) have found that 4% of morbidly obese individuals display a genetic mutation in the melanocortin-4 receptor (MC4), which plays a key role in the hypothalamic control of food intake. Thus, research into the MC4 receptor and other potential genetic causes of obesity continues at a rapid pace (Comuzzie & Allison, 1998). Environmental Contributors Poston and Foreyt (1999) have recently argued that genes are not the answer to understanding the development of obesity. They maintain that animal models of obesity are severely limited in their generalizability to humans. Moreover, they contend that several sources of information indicate that environmental factors are the primary determinants of human obesity. Environments that offer unlimited access to high-calorie foods and simultaneously support low levels of physical activity can promote obesity even in the absence of a specific genetic predisposition. As several authors (Hill & Peters, 1998; Poston & Foreyt, 1999) have noted, the human gene pool has not changed in the past quarter century. Consequently, the increased prevalence of obesity in the United States and other Western countries must be due to the influence of environmental factors on energy consumption and/or energy expenditure. We are surrounded by a toxic environment that promotes the overconsumption of energy-dense, nutrient-poor food (Battle & Brownell, 1996; Kant, 2000). The temptation to eat is virtually everywhere. Tasty, low cost, high-calorie items are readily available not only at fast-food restaurants, but also in supermarkets, food courts, vending machines, and even 24-hour service stations. In addition, larger portion sizes, supersizing, value meals, and 2-for-1 deals, all provide increased opportunities for excess consumption. We are eating more meals outside the home and in doing so they are consuming larger portions of food. In the early 1970s, about 20% of the household food dollar was spent on food outside the home but by 1995 that amount had doubled 7 to 40% (Putnam & Allshouse, 1996). Importantly, eating away from home, particularly at fast-food restaurants, is associated with higher energy intake and with higher fat intake (French, Harnack, & Jeffery, 2000). Thus, it is not surprising that studies have shown eating out to be a significant contributor to weight gain and the increasing prevalence of overweight (Binkley, Eales, & Jekanowski, 2000; McCrory et al., 1999). Physical inactivity also appears to be a significant contributor to overweight and obesity. Few occupations now require vigorous levels of physical activity. Moreover, labor-saving devices such as cars, elevators, escalators, motorized walkways, and remote controls, have had a significant cumulative impact in decreasing daily energy expenditure (Hill,Wyatt, & Melanson, 2000; James, 1995). In addition, energy expended in leisure-time activities has decreased as people spend more time sitting passively in front of televisions, VCRs/DVD players, and computers rather than participating in physical activities that require movement and greater amounts of energy expenditure. According to the Surgeon General (U.S. Department of Health and Human Services, 1996), 54% of the U.S. population engages in little or no leisure-time physical activities and fewer than 10% of Americans regularly participate in vigorous physical activity. Cross-sectional population studies typically show an inverse relationship between physical activity and body weight (DiPietro, 1995). Lower body weights and lower BMIs are associated with higher levels of self-reported physical activity. The findings appear strongest for high-intensity physical activities (presumably due to more accurate reporting of vigorous activities such as jogging). However, in cross-sectional studies, it is sometimes difficult to determine the direction of cause-and-effect relationships. While physical activity may affect body weight, it is also likely that body weight impacts physical activity via increased discomfort associated with higher body weight, including higher levels of breathlessness and sweating, and general difficulty in negotiating body movement. Many obese individuals also report embarrassment at being seen exercising (Ball, Crawford, & Owen, 2000). Longitudinal cohort studies may provide a better perspective on the cause-and-effect relationship between physical activity and body weight. For example, in the Male Health Professionals Study, Coakley et al. (1998) examined the impact of changes in activity on body weight in a prospective cohort study of 19,478 men. The researchers found that over the course of a four-year period, vigorous activity was associated with weight reduction, whereas sedentary behavior (TV/VCR viewing) and eating between meals were associated with weight gain. Men who increased their exercise, decreased TV viewing, and stopped eating between meals, lost an average weight of 1.4 kg compared to a weight gain of 1.4 kg among the overall population. Furthermore, the prevalence of obesity was lowest among men who maintained a relatively high level of vigorous physical activity, compared to those who were relatively sedentary. These data show that increased physical activity may prevent weight gain. 8